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ICSE 2022
Sun 8 - Fri 27 May 2022

The problem of flakiness occurs when a test case is non-deterministic and exhibits both a passing and failing behavior when run against the same code. Over the last years, the software engineering research community has been working toward defining approaches for detecting and addressing test flakiness, but most of these approaches suffer from scalability issues. Recently, this limitation has been targeted through machine learning solutions that could predict flaky tests using various features, both static and dynamic. Unfortunately, the proposed solutions involve features that could be costly to compute. In this paper, I perform a step forward and predict test flakiness \emph{only using statically computable metrics.} I conducted an experiment on 18 projects coming from the \textsc{FlakeFlagger} dataset. First, I statistically assess the differences between flaky and non-flaky tests in terms of 25 static metrics in an individual and combined way. Then, I experimented with a machine learning approach that predicts flakiness based on the previously evaluated factors. The results show that static features can be used to characterize flaky tests: this is especially true for metrics and smells connected to source code complexity. In addition, this new static approach has performance comparable to the machine learning models already in the literature in terms of F-Measure.

Tue 24 May

Displayed time zone: Eastern Time (US & Canada) change

13:00 - 15:00
Poster round: GraduatesSRC - ACM Student Research Competition at Student Research Competition room

Judges

  • Valentina Lenarduzzi
  • Mahmoud Hammad
  • Christoph Matthies
  • Sira Vegas
  • Julian Dolby
  • Alexander Serebrenik
  • Luciano Baresi
  • Pasqualina Potena
  • Fernanda Madeiral
14:00
2h
Woodpecker: Identifying and Fixing Android UI Display Issues
SRC - ACM Student Research Competition
Zhe Liu Institute of Software, Chinese Academy of Sciences
14:00
2h
Static Test Flakiness Prediction
SRC - ACM Student Research Competition
Valeria Pontillo University of Salerno
14:00
2h
Finding Appropriate User Feedback Analysis Techniques for Multiple Data Domains
SRC - ACM Student Research Competition
Peter Devine The University of Auckland
14:00
2h
Short-paper
Efficiently and Precisely Searching for Code Changes with DiffSearch
SRC - ACM Student Research Competition
Luca Di Grazia University of Stuttgart
Link to publication DOI File Attached
14:00
2h
An Empirical Study on the Current Adoption of Quantum Programming
SRC - ACM Student Research Competition
Manuel De Stefano Università di Salerno

Information for Participants
Tue 24 May 2022 13:00 - 15:00 at Student Research Competition room - Poster round: Graduates
Info for room Student Research Competition room:

Please check how to access the room here